papers

Publications (27)

cs.RO2025

Morphological Cognition: Classifying MNIST Digits Through Morphological Computation Alone

Alican Mertan, Nick Cheney

With the rise of modern deep learning, neural networks have become an essential part of virtually every artificial intelligence system, making it difficult even to imagine differen…

cs.RO2025

Controller Distillation Reduces Fragile Brain-Body Co-Adaptation and Enables Migrations in MAP-Elites

Alican Mertan, Nick Cheney

Brain-body co-optimization suffers from fragile co-adaptation where brains become over-specialized for particular bodies, hindering their ability to transfer well to others. Evolut…

cs.NE2013

Hands-free Evolution of 3D-printable Objects via Eye Tracking

Nick Cheney, Jeff Clune, Jason Yosinski +1

Interactive evolution has shown the potential to create amazing and complex forms in both 2-D and 3-D settings. However, the algorithm is slow and users quickly become fatigued. We…

q-bio.OT2025

The Genomic Code: The genome instantiates a generative model of the organism

Kevin J. Mitchell, Nick Cheney

How does the genome encode the form of the organism? What is the nature of this genomic code? Inspired by recent work in machine learning and neuroscience, we propose that the geno…

cs.RO2023

Modular Controllers Facilitate the Co-Optimization of Morphology and Control in Soft Robots

Alican Mertan, Nick Cheney

Soft robotics is a rapidly growing area of robotics research that would benefit greatly from design automation, given the challenges of manually engineering complex, compliant, and…

cs.LG2024

Continual learning under domain transfer with sparse synaptic bursting

Shawn L. Beaulieu, Jeff Clune, Nick Cheney

Existing machines are functionally specific tools that were made for easy prediction and control. Tomorrow's machines may be closer to biological systems in their mutability, resil…